Paddle + Bruin
Ingest Paddle data into your warehouse with incremental loading, quality checks, and full lineage. Defined in YAML, version-controlled in Git.
For business teams
What you get
Revenue reporting you can audit
Paddle transaction data flows into your warehouse with quality checks that validate amounts, currencies, and reconciliation — every single sync.
MRR/ARR calculated right
Combine Paddle with subscription data to automate MRR, ARR, and churn calculations. Finance gets numbers, not guesswork.
Catch issues before close
Quality checks flag missing transactions, amount mismatches, and anomalies. Finance finds out from Bruin, not from the CFO.
Unified financial view
Join Paddle with your ERP, CRM, and other financial tools. One source of truth for revenue, not five spreadsheets.
For data & engineering teams
How it works
Idempotent incremental loads
Re-runs are safe. Bruin's merge strategy ensures Paddle transactions are never duplicated, even on retry.
YAML-defined, Git-versioned
Your Paddle pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert. Auditors love this.
Reconciliation checks
Custom SQL checks validate that amounts balance and currencies match. Pipeline stops if something doesn't add up.
Multi-destination support
Land Paddle data in BigQuery, Snowflake, Redshift, or DuckDB. Switch destinations by changing one line.
Before you start
Step 1
Add your Paddle connection
Connect using Paddle API credentials. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.
Parameters
api_keyPaddle API authentication keyvendor_idPaddle vendor identifier
connections:
paddle:
type: paddle
uri: "paddle://api_key@vendor_id"Step 2
Create your pipeline
Define a YAML asset that tells Bruin what to pull from Paddle and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.
Available tables
name: raw.paddle_subscriptions
type: ingestr
parameters:
source_connection: paddle
source_table: 'subscriptions'
destination: bigquery
# Syncs transactions, invoices, and payment
# data with idempotent incremental loads.Step 3
Add quality checks
Validate Paddle data on every sync. Catch amount mismatches, missing currencies, and reconciliation failures before they reach finance reports.
columns:
- name: id
checks:
- name: not_null
- name: unique
- name: amount
checks:
- name: not_null
- name: currency
checks:
- name: not_null
custom_checks:
- name: amounts balance
query: |
SELECT ABS(SUM(CASE WHEN type = 'credit'
THEN amount ELSE -amount END)) < 0.01
FROM raw.paddle_subscriptions
WHERE created_at > CURRENT_DATE - 1Step 4
Run it
One command. Bruin connects to Paddle, pulls data incrementally, runs your quality checks, and lands clean data in your warehouse. If a check fails, the pipeline stops — bad data never reaches downstream.
--start-date$ bruin run .Running pipeline...
paddle_subscriptions
✓ Fetched 2,847 new records
✓ Quality: campaign_id not_null PASSED
✓ Quality: spend not_null PASSED
✓ Quality: no negative ad spend PASSED
✓ Loaded into bigquery
Completed in 12sReady to connect Paddle?
Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.